Next Article in Journal
Quadratic Forms in Random Matrices with Applications in Spectrum Sensing
Next Article in Special Issue
As One and Many: Relating Individual and Emergent Group-Level Generative Models in Active Inference
Previous Article in Journal
Transient Voltage Information Entropy Difference Unit Protection Based on Fault Condition Attribute Fusion
Previous Article in Special Issue
Refining the Allostatic Self-Efficacy Theory of Fatigue and Depression Using Causal Inference
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Entropy
Volume 27
Issue 1
10.3390/e27010062
entropy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models

by
Samuel William Nehrer
1,†,
Jonathan Ehrenreich Laursen
1,†,
Conor Heins
2,3,*,
Karl Friston
3,4,
Christoph Mathys
5 and
Peter Thestrup Waade
5
1
School of Culture and Communication, Aarhus University, 8000 Aarhus, Denmark
2
Department of Collective Behaviour, Max Planck Institute of Animal Behavior, D-78457 Konstanz, Germany
3
VERSES Research Lab., Los Angeles, CA 90016, USA
4
Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
5
Interacting Minds Centre, Aarhus University, 8000 Aarhus, Denmark
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Entropy 2025, 27(1), 62; https://doi.org/10.3390/e27010062
Submission received: 25 October 2024 / Revised: 2 January 2025 / Accepted: 7 January 2025 / Published: 12 January 2025
(This article belongs to the Special Issue From Functional Imaging to Free Energy—Dedicated to Professor Karl Friston on the Occasion of His 65th Birthday)
Browse Figures
Versions Notes

Abstract

We introduce a new software package for the Julia programming language, the library ActiveInference.jl. To make active inference agents with Partially Observable Markov Decision Process (POMDP) generative models available to the growing research community using Julia, we re-implemented the pymdp library for Python. ActiveInference.jl is compatible with cutting-edge Julia libraries designed for cognitive and behavioural modelling, as it is used in computational psychiatry, cognitive science and neuroscience. This means that POMDP active inference models can now be easily fit to empirically observed behaviour using sampling, as well as variational methods. In this article, we show how ActiveInference.jl makes building POMDP active inference models straightforward, and how it enables researchers to use them for simulation, as well as fitting them to data or performing a model comparison.
Keywords: active inference; free energy principle; predictive processing; Markov decision process; cognitive modelling; Julia active inference; free energy principle; predictive processing; Markov decision process; cognitive modelling; Julia

Share and Cite

MDPI and ACS Style

Nehrer, S.W.; Ehrenreich Laursen, J.; Heins, C.; Friston, K.; Mathys, C.; Thestrup Waade, P. Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models. Entropy 2025, 27, 62. https://doi.org/10.3390/e27010062

AMA Style

Nehrer SW, Ehrenreich Laursen J, Heins C, Friston K, Mathys C, Thestrup Waade P. Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models. Entropy. 2025; 27(1):62. https://doi.org/10.3390/e27010062

Chicago/Turabian Style

Nehrer, Samuel William, Jonathan Ehrenreich Laursen, Conor Heins, Karl Friston, Christoph Mathys, and Peter Thestrup Waade. 2025. "Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models" Entropy 27, no. 1: 62. https://doi.org/10.3390/e27010062

APA Style

Nehrer, S. W., Ehrenreich Laursen, J., Heins, C., Friston, K., Mathys, C., & Thestrup Waade, P. (2025). Introducing ActiveInference.jl: A Julia Library for Simulation and Parameter Estimation with Active Inference Models. Entropy, 27(1), 62. https://doi.org/10.3390/e27010062

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop